Secondary structure propensity

Figure 1. Most cx)mmon (consensus) sequences of the two types of sea anemone toxins. Bold letters represent residues which both toxin types have in common. Letters above each sequence are nonconservative substitutions, while letters below each sequence are conservative substitutions. A nonconservative substitution was defined as one in which (a) electronic charge changed, (b) a hydrogen-bonding group was introduced or removed, (c) the molecular size of the sidechain was changed by at least 50%, or (d) the secondary structure propensity was changed drastically from b to h or vice versa (Ref.

Sidechain conservatism may be split up into at least two kinds 1) substitutions which conserve sidechain bonding forces - providing similar electrostatic, hydrophilic, or hydrogen bonding interactions, and 2) substitutions conserving secondary structure propensity. For instance, substitution of glutamic acid with aspartic acid conserves charge, but this could have a considerable effect upon the secondary structure propensity of the peptide. 

One of the interesting questions is why this approach has not been reported to have been used to successfully identify new members of other families of cytokines, such as the four helix bundle family which includes IL-2, IL-4, IL-5, etc. One problem for these families is that the defining features are not so apparent (for example the positions of the disulfide bonds are not always conserved). Also, the majority of the members of these cytokine families are only finally confirmed once their three-dimensional structures have been solved. It may be that when more sophisticated versions of such techniques as Profile searching can be used will this then open up new cytokines for more classical families. Such Profiles would have to include amino acid similarities, as well as secondary structure propensity. Even so, the current rate of success is not expected to be as high as for the chemokine area (see, for example, ref. 15). 

Bahar I, Kaplan M, Jernigan RL (1997) Short-range conformational energies, secondary structure propensities, and recognition of correct sequence-structure matches. Proteins 29 292-308... 

Fig. 13.6. Calculated vs. observed changes in aggregation rates upon mutation. The experimental data relate to mutations of short peptides or natively unfolded proteins including amylin, the A(3-peptide and a-synuclein. The calculated values are determined from an equation involving the changes in just three variables -hydrophobicity, charge and secondary structure propensities - caused by the mutations. The plot shows, for both experimental and calculated data, In (umut/vwt), he., the natural logarithm of the aggregation rate of the mutant umut divided by that of the wild-type molecule vwt. From [36]...

Volume = Volume enclosed by van der Waals radii Mass = molecular weight of nonionized amino acid minus that of water both adopted from Creighton (1993) HP scale = degree of hydrophobicity of amino acid side chains, based on Kyte Doolittle (1982) Surface Area = mean fraction buried, based on Rose et al. (1985) and Secondary structure propensity = the normalized frequencies for each conformation, adopted from Creighton (1993), is the fraction of residues of each amino acid that occurred in that conformation, divided by this fraction for all residues. 

Pawar et al. were able to show that the generic factors affecting amyloidosis are hy-drophobicity, secondary structure propensity and charge and used these to create intrinsic Z-scores for aggregation of any polypeptide, enabling calculation and comparisons between different polypeptide sequences (Pawar et al. 2005). 

Xiong and co-workers (1995) carried out an elegant experiment to assess the significance of the intrinsic secondary-structure propensity of the amino acid residues relative to periodicity in the peptide sequence the experiment was designed to favour another secondary structure. Four peptides were prepared with their periodicity favouring either an a-helical or P-strand secondary structure. Their constituent amino acids were chosen to either reinforce or work against this periodicity. 

Residual dipolar couplings have been calculated for four disordered proteins of difierent sizes with secondary structure propensities by Forman-Kay and co-workers using local alignment tensors and compared with the measured RDCs. Using simulations of RDCs in partially unfolded polyalanine chains Jensen and Blackledge have shown that the appearance of the NMR dipolar waves may provide information on the behaviour of the neighbouring capping strands. Bryson et have presented... 

Figure 9 Schematic of a neural network, (a) An individual neuron is characterized by its input weights and its output threshold, (b) Several neurons combined in a net serve to generate an output state from an input state vector. The input might be a sequence and the output a classification of that sequence according to its secondary structural propensity. A hidden layer in between input and output may further modulate the response...

In this section we discuss mainly three types of potential terms computed from statistical analyses (Figure 2) (a) the residue-residue interaction potentials considered to represent local and nonlocal interactions between residues along the polypeptide chain (b) the local backbone potential, representing local interactions such as those associated with secondary structure propensities and (c) the profile-like potentials, considered to represent the interactions of individual residues with their three-dimensional environment. In contrast to molecular mechanics force fields, which have converged to a small number of functional forms and parameter sets, the implementations of these various potentials remain rather diverse. In the following we illustrate these implementations with some specific examples, and use these as the basis to review the approaches taken by various authors. 

In the latter implementation, the residue interaction potentials measure the propensities P l °j (dij) of amino acid pairs at positions / and j along the sequence to be separated by a given spatial distance d. Residue pairs are partitioned according to the number of positions / — j that separates them along the polypeptide sequence. In order to try and distinguish between local contributions associated with secondary structure propensities and nonlocal tertiary interactions, pairs of consecutive residues are not considered, because their spatial distance is roughly constant. For pairs separated by 2-8 sequence positions (1 < f — j < 8), probabilities are computed for each separation individually, yielding seven... 

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